RADAR INTERFEROMETRY FOR SAFE COAL MINING IN CHINA
L. Ge a, H.-C. Chang a, A. H. Ng b and C. Rizos a
Cooperative Research Centre for Spatial Information
School of Surveying & Spatial Information Systems, The University of New South Wales, Sydney, Australia
a
(l.ge, hc.chang, c.rizos)@unsw.edu.au; balex.ng@student.unsw.edu.au
Commission VII, WG VII/2
KEY WORDS: DInSAR, Mining, Ground Deformation Monitoring, SAR
ABSTRACT:
Land surface deformation due to underground mining is always a concern to the local communities and environment. The
underground coal mines at the study site in Northern China are located quite closely to each other. In order to ensure safe mining as
well as to prevent illegal mining activities, differential radar interferometry (DInSAR) was introduced for monitoring mine
subsidence. The spaceborne SAR data acquired by ENVISAT (C-band) and ALOS (L-band) were tested in this paper. The limits of
radar interferometry were discussed by addressing the issues of decorrelation and deformation phase gradient. The ALOS results
show it is more suitable for monitoring the rapid and large land deformation due to underground mining. However, the data acquired
in summer season (June – September) have higher noise, which may be caused by the local agriculture.
1. INTRODUCTION
2. METHODOLOGY
Land deformation caused by underground mining becomes
more and more a concern for many areas in China. Especially
the population density in China is very high by comparing with
many other countries. In order to ensure safe mining as well as
to prevent illegal mining activities, the implementation of an
effective mining monitoring scheme is important. Conventional
subsidence monitoring measurement is done by precision digital
levels, total stations and GPS receivers. Both digital level and
total station can deliver 0.1 mm in height resolution while GPS
can sense 5 mm changes in static mode. However, applying
leveling and GPS surveys over a large area are not just labour
intensive, but also very time consuming. Ideally, the mine
subsidence should be carefully monitored with a surveying
network. However, surveying over the entire network may take
a few weeks. The coverage of the surveying network may also
be limited due to site accessibility. The maintenance of the
survey marks are another important and yet difficult issue.
Differential radar interferometry (DInSAR) technique has been
demonstrated its capability of monitoring land subsidence (Ge
et al., 2007). DInSAR can monitor the land deformation at subcentimetre accuracy over a large area (at the radar swath width
of 50~100km). D-InSAR method is a land deformation mapping
technology, which is complementary to other surveying
methods.
Repeat-pass spaceborne DInSAR is used here to derive ground
displacement maps. The basic theory of radar interferometry
can be found in great details in (Bamler and Hartl, 1998;
Gabriel et al., 1989; Rosen et al., 2000; Zebker and Goldstein,
1986). In short, two SAR images acquired from two slightly
different positions, at different times, are used to measure the
phase difference, or so-called interferogram, between the two
acquisitions. Interferogram consists of topographic information,
land deformation occurred between the two acquisitions,
atmospheric disturbances, orbit errors and noise. DInSAR is the
process to measure the phase variation due to land deformation
by eliminating or minimising the other components. The
topographic phase contribution can be simulated by introducing
a digital elevation model (DEM). A 3 arc-second SRTM DEM
(approximately 90m resolution) is used in this paper to simulate
the topographic phase, which can be removed from the
interferogram. The atmospheric component is primarily due to
fluctuations of water vapour in the atmosphere between the
satellite and the ground. The atmospheric delay can be
identified using the fact that its fringe structure is independent
over several interferograms, or can be modelled by using a GPS
network (Ge et al., 2003 & 2004). As the volume of the water
vapour in the atmosphere varies with low spatial frequency, it is
sometimes negligible in the applications such as mining
subsidence monitoring where the spatial frequency is much
higher.
The test site in this study locates in the middle of Huabei plain,
China. It covers about 570km2. The mine has been excavated
since early 20th century. Today, the region is one of the most
important coal mining areas in China, producing about 2,700
million tones of coal per year. There are about 500 collieries
built up in this region, and some new collieries are planned to
be constructed in the near feature. As a result, the region has
been environmentally degraded. And the subsidence is expected
to become more severe in the future. The land-use is a mixture
of villages and farmlands of wheat and corns.
In the differential interferogram a complete 2π phase change is
equivalent to a height displacement of half of the wavelength of
the radar signal in the slant range direction. That is 11.75cm for
JERS-1 and ALOS L-band data. Since the measured phases in
the interferogram are wrapped in modulo of 2π, the height
displacement map can be derived by ‘phase unwrapping’ the
interferogram. Finally the unwrapped phase can be converted to
height change.
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interferometric pair for DInSAR processing is therefore
preferred to be as small as possible.
3. INPUT DATA
ENVISAT and ALOS SAR imagery were tested using DInSAR
for monitoring the ground deformation due to mining at the
study area shown in Table 1. The spatial and temporal
separations between the images of the interferometric pair are
indicated as perpendicular baseline (Bperp) and temporal
baseline (Btemp).
Sensor
ALOS /
PALSAR
ENVISAT
/ ASAR
Master
(dd/mm/yyyy
)
14/6/2007*
30/7/2007*
15/12/2007**
Slave
(dd/mm/yyyy
)
30/7/2007*
14/9/2007*
30/01/2008**
Bperp
(m)
Btemp
(day)
515
143
351
46
46
46
3/1/2008
7/2/2008
361
35
Temporal decorrelation is caused by the variation of the
dielectric properties of ground objects over time between two
repeat-pass acquisitions. In repeat-pass interferometry the subresolution properties of the imaged scatterers (sub-scatterers)
may change between surveys, e.g. by meteorological
differences at the time of image acquisitions, the movement of
leaves and branches, water surface, or vegetation growth.
Therefore, urban regions normally illustrate much higher
coherence than vegetated/agricultural areas over a period of
time.
Volume decorrelation is also about the phase stability of the
imaging cell (pixel) over time, especially over vegetated
regions. The dielectric properties and alignments of tree leaves
and branches in the canopy may result in the variation of the
backscattered radar signals. They are also affected easily by the
local weather conditions, such as rains and winds. Therefore, it
is desirable to have a finer SAR imaging resolution in order to
minimise the variation of the random scattering phases.
Table.1. Interferometric pairs tested using DInSAR for
monitoring mine subsidence at the study area. Note: * and **
denote the ALOS data acquired in single and dual polarization
mode, respectively.
The histograms of the coherence value of 4 selected
interferometric pairs as given in Table 1 are shown in Figure 1.
The mean coherence of the ALOS pair, 15/12/2007 –
30/01/2008, illustrated higher value than other two ALOS pairs
acquired in June, July and September in 2007.
4. LIMITATIONS OF DINSAR MEASUREMENT
Radar interferometry is the technique to measure geodetic
information, e.g. elevation or height change, by exploiting the
phase information of at least two images. The precision of the
result depends on not only the wavelength of the microwave
signals emitted by the SAR antenna, but also the geometry of
interferometric pair. Shorter wavelengths are more sensitive to
the height change of terrain than the longer wavelengths.
However, the shorter wavelengths can be more influenced by
vegetations. Geometry of interferometric pair determines the
sensitivity of interferometric phases with respect to topography.
After all, the precision of radar interferometry depends on how
accurate the process is to convert the interferometric phases to
height or height changes. The limitations of DInSAR
measurement are discussed in the following subsections.
It is interesting to note that even the perpendicular baseline of
the ALOS pair, 30/7/2007 – 14/9/2007, is 143m its coherence
over the selected scene is not as good as expected. After
comparing this coherence map to a high resolution optical
image of the identical area, the areas showing low coherence
value (<0.3) are actually farmlands. It suggests the local
agriculture pattern may cause additional noise in the scene.
Based on the coherence value shown in Figure 1, the
decorrelation due to agriculture is more severe in summer (June
– September) than winter (December – February). In addition,
the ALOS data acquired on 15/12/2007 and 30/01/2008 are in
single polarization mode, which has twice better imaging
resolution than the images acquired in dual polarization mode.
Therefore, the interferometric pairs with better imaging
resolution will be less subject to volume decorrelation, hence
high interferometric coherence value.
4.1 Decorrelation
The interferometric quality of an identical imaging pixel in two
SAR images can be assessed by measuring the correlation
between the pixels. The quantity of correlation, or the so-called
coherence, can be considered as a direct measure for the
similarity of the dielectric properties of the same imaging pixels
between two SAR acquisitions. Decorrelation degrades the
coherence between two SAR images and results phase noise.
The ENVISAT pair covers a similar period as the 3rd ALOS
pair. However, it has less mean coherence of 0.379. The
decorrelation may be caused by the spatial decorrelation as the
perpendicular baseline of this ENVISAT pair is about 361m.
4.2 High phase gradient
Decorrelation is site-specific. It depends upon local climate
conditions, vegetation cover, complexity of the terrain
(moderate v.s. hilly or mountainous), land use, etc. As a rule of
thumb, decorrelation is more severe for the area having heavily
vegetated cover, complex terrain or constantly changing climate
conditions. Decorrelation can be classified into three main
categories: spatial, temporal and volume decorrelation (Zebker
and Villasenor, 1992).
As mentioned earlier, the interferometric phase variation caused
by land deformation is linearly depending on the height change
of terrain. Therefore, a large vertical ground movement over a
small spatial extent causes the rapid changes of phases in the
differential interferogram. When the phase gradient gets too
large, it becomes ambiguous and it is impossible to recover the
height change accurately. The problem can be solved or
reduced by having interferometric pairs with higher imaging
resolution, signals with longer wavelength and/or a shorter site
revisit cycle. This is demonstrated in Figure 2 by comparing the
DInSAR results derived using ENVISAT (C-band, wavelength
= 5.6cm) and ALOS (L-band, wavelength = 23.5cm) data.
Spatial decorrelation is caused by the physical separation, or socalled perpendicular baseline, between the locations of the two
SAR antennas. The maximum allowable baseline before the
pixels get totally decorrelated is often referred to as the critical
baseline (Zebker et al., 1994). The perpendicular baseline of the
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For the same amount of ground deformation, the induced
DInSAR phase fringes will be denser in the results generated
using shorter radar wavelength (e.g. C-band) than the ones
generated using longer wavelength (e.g. L-band). Figure 2 (a)
shows the high phase gradient within the subsidence bowl
causing the phase ambiguous. As a result, the phase fringes
cannot be fully recovered, even after being filtered.
(a)
5. RESULTS AND DISCUSSIONS
The study area is about 24km x 25km. The differential
interferograms of the selected four interferometric pairs (3 from
ALOS and 1 from ENVISAT) are shown in Figure 3. In the
results, over 21 mine subsidence spots are identified using
DInSAR technique. The magnitude of ground deformation due
to underground mining can be more accurately measured or
recovered if the interferometric pair illustrates high coherence
over the scene and at the same time the deformation phases are
not ambiguous. In this study, the ALOS pair with the mean
coherence value of 0.586 shows the deformation fringes quite
clearly as shown in Figure 2 (b).
Figure 4 shows the final deformation map derived from the
ALOS pair, 15/12/2007 - 30/01/2008. The result is overlaid on
a high resolution optical image with the aid of geographic
information systems (GIS). The maximum subsidence detected
due to active underground mining activities over a period of 46
days is about 36cm.
(b)
There are several coal collieries in the local area and they are
closely located to each other. Even though the proposed mining
location and mining schedule are recorded, it is still hard to
track the precise locations of mining activities. But it is
extremely important for ensuring the safety of the miners as
well as the local residents when the mining progress at the two
collieries are close to each other. The results of DInSAR
derived from successive acquisitions were post-analysed against
other supporting spatial data in geographic information systems
(GIS). By comparing the locations against the proposed mining
schedule, any illegal mining activities can also be identified.
(c)
(d)
Figure 1. Histograms of coherence values of (a) - (c) ALOS
interferometric pairs: 14/6/2007 - 30/7/2007 Bperp = 515m,
30/7/2007 - 14/9/2007 Bperp = 143m, and 15/12/2007 30/01/2008 Bperp = 351m, and (d) ENVISAT pair: 3/1/2008 7/2/2008 Bperp = 361m, respectively. The mean coherence
value of these 4 pairs are 0.355, 0.461, 0.586 and 0.379.
6. CONCLUDING REMARKS
(a)
This paper demonstrated the capability of differential radar
interferometry (DInSAR) for monitoring the ground surface
deformation caused by underground mining activities. The
study area chosen in this paper is in the Northern China.
ENVISAT and ALOS SAR data acquired in C- and L-band
respectively were tested in this paper. Within an area of
approximately 24km x 25km, more than 20 subsidence spots
are identified using DInSAR. The results show ALOS data are
more suitable for mine subsidence monitoring. The L-band
radar signal and the high imaging resolution (8m) of ALOS
reduce the problems caused by high deformation phase gradient
and improve the scene coherence. It is also found that the local
agricultural areas may introduce noises into the interferometric
results, especially during summer season. Nevertheless, the area
of impact of mine subsidence at multiple collieries can be
monitored at the same time using DInSAR. The DInSAR
deformation map is complementary to the ground surveys and
assists to identify any abnormal subsidence behaviour. Together
with other spatial data, it helps to ensure the safety of the local
communities as well as the mine workers.
(b)
Figure 2. Enlarged DInSAR phase fringes induced by ground
deformation of (a) ENVISAT (C-band) pair: 3/1/2008 7/2/2008 Bperp = 361m, and (b) ALOS (L-band) pair:
15/12/2007 - 30/01/2008 Bperp = 351m.
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(a)
(b)
(c)
(d)
Figure 3. DInSAR interferograms of (a) – (c) ALOS interferometric pairs: 14/6/2007 - 30/7/2007 Bperp = 515m, 30/7/2007 14/9/2007 Bperp = 143m, and 15/12/2007 - 30/01/2008 Bperp = 351m, and (d) ENVISAT pair: 3/1/2008 - 7/2/2008 Bperp = 361m
respectively.
ACKNOWLEDGEMENTS
This research work is supported by the Cooperative Research
Centre for Spatial Information (CRC-SI) through Project 4.09,
whose activities are funded by the Australian Commonwealth’s
Cooperative Research Centres Programme. The authors wish to
thank the European Space Agency (ESA) for providing the
ENVISAT data. ALOS interferograms were processed under
CRC-SI project 4.09, including material copyright METI and
JAXA (2006-2008) L-1.1 product: produced by ERSDAC.
METI and JAXA have the ownership of the PALSAR original
data. ERSDAC produced and distributed the PALSAR L-1.1
product. The PALSAR L-1.1 products were distributed to the
IAG Consortium for Mining Subsidence Monitoring. The
authors are grateful to ERSDAC for their support of the
consortium.
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